PROJECT SUMMARY Glaucoma is the leading cause of irreversible blindness and visual impairment in the world. As the disease generally remains asymptomatic until late stages, early detection of functional damage is paramount, so that treatment can be initiated or advanced in order to avoid progression to disability. Detection of functional loss is traditionally made with standard automated perimetry (SAP). However, SAP testing is limited by subjectivity of patient responses and large variability, requiring a large number of tests for detection of change over time. These tests are conducted in clinic-based settings and, due to limited patient availability and health care resources, insufficient tests are usually acquired over time, resulting in delayed detection of progression. The requirement for highly trained technicians, cost, complexity, and lack of portability of SAP also preclude its use for screening of visual field loss in underserved populations. To address shortcomings of current methods to assess visual function, we have developed an innovative brain-computer interface (BCI) that allows portable and objective assessment of visual function loss through multifocal steady-state visual-evoked potentials (mfSSVEP). The BCI consists of a wearable device employing a head-mounted display (HMD) integrated with wireless electroencephalography (EEG). In cross-sectional investigations, we demonstrated that the BCI mfSSVEP parameters were able to successfully detect glaucomatous damage with excellent test-retest repeatability. Based on the encouraging results of the preliminary studies, we now propose a multicenter investigation of the ability of longitudinal BCI mfSSVEP parameters in detecting glaucoma progression. In Specific Aim 1, we will collect longitudinal BCI mfSSVEP data during clinic-based visits in glaucoma patients and healthy subjects. We hypothesize that BCI mfSSVEP data will be able to successfully detect progression and measure rates of change, as compared to functional assessment by SAP and structural assessment by optical coherence tomography. In Aim 2, we will collect home-based longitudinal mfSSVEP data and investigate their performance for detecting glaucoma progression and measuring rates of change. We hypothesize that the increased frequency of testing from home-based BCI testing will result in earlier detection and prediction of progression compared to clinic- based data and conventional testing. In Aim 3, we will investigate the ability of BCI mfSSVEP data in predicting patient-reported quality of life in glaucoma. In summary, this proposal employs a highly innovative BCI device to acquire longitudinal mfSSVEP data with the central aim of improving detection and prediction of glaucoma progression. The approach has the potential to address major current limitations of standard testing, significantly impacting management of the disease. Objective home-based testing of visual function could represent a transformative way of diagnosing and monitoring progression.